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Technology product evolution and the diffusion of new product features

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  • Kivi, Antero
  • Smura, Timo
  • Töyli, Juuso

Abstract

The evolution of technology products can be analysed on multiple levels. Product categories go through continuous evolution determined by the cumulative changes in the features of new product models. This is manifested in the diffusion of new product features and in the increasingly vague boundaries between different product generations. This article develops an approach for planning and forecasting technology product evolution and the diffusion of new product features. This is achieved by isolating the phenomena underlying the evolution process, and formulating the process at the product category, product feature, and product model levels. The approach is derived from these formulations combining the primarily demand-driven product category diffusion and product unit replacement behaviour, and the more supply-driven product feature dissemination. The approach enables meaningful sensitivity analysis including the analysis of discontinuities. The developed approach is applied to characterise the evolution of an example product category of mobile handsets and to forecast the diffusion of mobile handset features using extensive longitudinal and cross-sectional data collected from Finland. In consequence, the process of technology product evolution and the phenomenon of product feature dissemination are suggested as extensions to research on product category diffusion and replacement.

Suggested Citation

  • Kivi, Antero & Smura, Timo & Töyli, Juuso, 2012. "Technology product evolution and the diffusion of new product features," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 107-126.
    • Handle: RePEc:eee:tefoso:v:79:y:2012:i:1:p:107-126
    DOI: 10.1016/j.techfore.2011.06.001
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    Cited by:

    1. Michelsen, Carl Christian & Madlener, Reinhard, 2016. "Switching from fossil fuel to renewables in residential heating systems: An empirical study of homeowners' decisions in Germany," Energy Policy, Elsevier, vol. 89(C), pages 95-105.
    2. Riikonen, Antti & Smura, Timo & Kivi, Antero & Töyli, Juuso, 2013. "Diffusion of mobile handset features: Analysis of turning points and stages," Telecommunications Policy, Elsevier, vol. 37(6), pages 563-572.
    3. Benseny, Jaume & Lahteenmaki, Jarno & Toyli, Juuso & Hammainen, Heikki, 2023. "Urban wireless traffic evolution: The role of new devices and the effect of policy," Telecommunications Policy, Elsevier, vol. 47(7).
    4. Yoon, Jungsub & Lee, Jeong-Dong & Hwang, Seogwon, 2022. "Episodic change: A new approach to identifying industrial transition," Technovation, Elsevier, vol. 115(C).
    5. Jaume Benseny & Jarno Lahteenmaki & Juuso Toyli & Heikki Hammainen, 2023. "Urban wireless traffic evolution: the role of new devices and the effect of policy," Papers 2310.14406, arXiv.org.
    6. Riikonen, Antti & Smura, Timo & Töyli, Juuso, 2016. "The effects of price, popularity, and technological sophistication on mobile handset replacement and unit lifetime," Technological Forecasting and Social Change, Elsevier, vol. 103(C), pages 313-323.
    7. Henna Warma & Tapio Levä & Howard Tripp & Alan Ford & Alexandros Kostopoulos, 2011. "Dynamics of communication protocol diffusion: the case of multipath TCP," Netnomics, Springer, vol. 12(2), pages 133-159, July.
    8. Vesselkova, Alexandr & Riikonena, Antti & Hämmäinena & Heikki, 2015. "Evolution of mobile handset feature dependences," 26th European Regional ITS Conference, Madrid 2015 127192, International Telecommunications Society (ITS).
    9. Kilkki, Kalevi & Mäntylä, Martti & Karhu, Kimmo & Hämmäinen, Heikki & Ailisto, Heikki, 2018. "A disruption framework," Technological Forecasting and Social Change, Elsevier, vol. 129(C), pages 275-284.
    10. Chul-Yong Lee & Sung-Yoon Huh, 2017. "Technology Forecasting Using a Diffusion Model Incorporating Replacement Purchases," Sustainability, MDPI, vol. 9(6), pages 1-14, June.

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